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Abstract:

A method and system for operating a facility having a plurality of
equipment combinations wherein each equipment combination is operating
interactively with at least one of another of the plurality of equipment
combination is provided. The method includes receiving, in real-time, for
each of the plurality of equipment combinations, a plurality of measured
process parameters, determining at least one derived quantity from the
plurality of measured process parameters, and recommending a change to an
equipment operation based on the measured process parameters and the
derived quantities.

Claims:

1-8. (canceled)

9. A method of analyzing the health of an equipment combination operating
in a system that includes a plurality of other equipment combinations
coupled to the equipment combination through conduits, and wherein the
equipment combination includes a driver machine and a driven machine
coupled in rotational synchronicity, said method comprises:receiving a
measured process parameter associated with the driver machine;receiving a
measured process parameter associated with the driven machine;receiving
at least one measured process parameter associated with the plurality of
other equipment combinations; andderiving a process parameter quantity
for at least one of the measured process parameter associated with the
driver machine and the measured process parameter associated with the
driven machine using the at least one measured process parameter
associated with the plurality of other equipment combinations.

10. A method of analyzing the health of an equipment combination in
accordance with claim 9 wherein deriving a process parameter quantity
comprises deriving a process parameter quantity for a parameter that is
not instrumented.

11. A method of analyzing the health of an equipment combination in
accordance with claim 9 wherein deriving a process parameter quantity
comprises deriving a process parameter quantity for a parameter that is
measured by at least one process sensor wherein the derived process
parameter quantity is compared to a respective measured process parameter
to verify an operability of the at least one sensor.

12. An integrated monitoring and control system for a plant wherein the
plant has a plurality of equipment combinations that are operable
interactively with each other and with individual equipment and wherein
the combinations are operable to maintain selected plant operational
conditions, said monitoring and control system comprising:a plurality of
sensors operatively coupled to the equipment combinations, the plurality
of sensors measuring process parameters for monitoring plant operation
and assessing equipment combination condition, and providing output
signals to said monitoring and control system;a derived quantity layer
communicatively coupled to a data bus, said derived quantity layer
configured to:receive the measured process parameters; andcompute values
for process parameters using the measured process parameters;a rule set
layer comprising at least one rule associated with at least some of the
plurality of equipment combinations for determining a health of the
equipment combination; anda recommendation layer for correlating the
health of the equipment combination to at least one of a mitigating
procedure, a maintaining procedure, and an operation procedure.

13. An integrated monitoring and control system for a plant in accordance
with claim 12 further comprising a communications layer for sampling said
sensor output signals communicatively coupled to the output signals.

14. An integrated monitoring and control system for a plant in accordance
with claim 13 wherein said communications layer is configured to receive
network message packets of sensor output data.

15. An integrated monitoring and control system for a plant in accordance
with claim 13 wherein said communications layer is configured to
preprocess said sensor output signals.

16. An integrated monitoring and control system for a plant in accordance
with claim 12 further comprising a display layer configured to generate
graphical representations of measured process parameters and derived
quantities.

17. An integrated monitoring and control system for a plant in accordance
with claim 16 wherein said display layer is configured to generate
graphical representations of measured process parameters and derived
quantities in at least one of real-time, historical values, and a
combination of real-time and historical values.

18. An integrated monitoring and control system for a plant in accordance
with claim 12 wherein said mitigating procedure includes selectable
control actions that are determined from a rule for at least one of
facilitating reducing damage to equipment from an equipment failure, and
maintaining the plant in an overall operational condition.

19. An integrated monitoring and control system for a plant in accordance
with claim 12 wherein said maintenance procedure includes maintenance
actions that are determined from a rule for at least one of facilitating
reducing an equipment outage time, increasing an equipment combination
availability, and facilitating reducing equipment combination failure.

20. A computer program embodied on a computer readable medium for
monitoring a plant, the plant having a plurality of equipment
combinations operating interactively with each other and with individual
equipment, said program comprising a code segment that controls a
computer that receives a plurality of process parameters from sensors
operatively coupled to the equipment combinations and individual
equipment and then:derives values for process parameters using the
measured process parameters;selects a rule from a set of rules comprising
a plurality of commands that direct data analysis for each at least one
of measured process parameter, a derived quantity, a plurality of
measured process parameters and a derived quantities associated with an
equipment combination; and recommends at least one of a mitigating
procedure, a maintaining procedure, and an operation procedure.

21. A computer program in accordance with claim 20 directs the computer to
receive a plurality of process parameters from a portable data collector.

22. A computer program in accordance with claim 20 directs the computer to
receive a plurality of process parameters from an online process monitor.

Description:

BACKGROUND OF THE INVENTION

[0001]This invention relates generally to the monitoring of machinery, and
more particularly to methods and systems for continuously monitoring a
plurality of machines.

[0002]At least some known machinery monitoring systems, monitor machine
drivers, for example, motors and turbines, or machine driven components,
such as, pumps, compressors, and fans. Other known monitoring systems
monitor process parameters of a process, for example, piping systems, and
machine environmental conditions, such as machine vibration, machine
temperature, and machine oil condition. Typically, such monitoring
systems are supplied by an original equipment manufacture (OEM) that is
responsible for only a portion of a facility, for example, a specific
piece of equipment, and as such, the OEM may only provide monitoring for
equipment provided by that OEM. However, industrial facilities such as
power plants, refineries, factories, and commercial facilities, such as,
hospitals, high-rise buildings, resorts, and amusement parks may utilize
a considerable plurality of machine drivers and driven equipment
dependently interconnected to form various process systems. An
architect/engineer may integrate such equipment for an owner or operator
of the facility. Monitoring systems supplied by different OEMs may
communicate with external data collection and control systems, such as
distributed control systems (DCS) located at sites that are remote from
the monitored equipment, for example, control rooms and/or operating
areas.

[0003]Typically, machine monitoring systems are primarily focused on
providing operating indications and controls, and/or trending or
datalogging capabilities for future reconstruction of abnormal events.
Machine monitoring systems that provide useful maintenance related data,
such as vibration data, limit data collection and analysis to discrete
components isolated from other components that may be operated in an
interconnected system. For example, monitoring systems may collect
vibration data for a motor/pump combination but, analyze each machine
separately, ignoring the interdependence between each individual machine.
If the analysis does account for the combination acting as a connected
combination, the known systems only consider the vibration parameters
collected, and any further analysis of external causes or sources for the
particular vibration characteristics of the motor/pump combination is
done manually by a plant engineer performing troubleshooting or
predictive maintenance activities. However, the motor/pump combination
may be part of a larger process system wherein any number of process
parameters from other motor/pump combinations and/or other equipment may
contribute or affect the vibration characteristics of the motor/pump
combination.

BRIEF DESCRIPTION OF THE INVENTION

[0004]In one aspect, a method and system for operating a facility having a
plurality of equipment combinations wherein each equipment combination is
operating interactively with at least one of another of the plurality of
equipment combination is provided. The method includes receiving, in
real-time, for each of the plurality of equipment combinations, a
plurality of measured process parameters, determining at least one
derived quantity from the plurality of measured process parameters, and
recommending a change to an equipment operation based on the measured
process parameters and the derived quantities.

[0005]In another aspect, an integrated monitoring and control system for a
plant having a plurality of equipment combinations operating
interactively with each other and with individual equipment wherein the
equipment combinations are operated to maintain selected plant
operational conditions is provided The integrated monitoring and control
system includes a plurality of sensors operatively coupled to the
equipment combinations, the plurality of sensors measuring process
parameters for monitoring plant operation and assessing equipment
combination condition, and providing output signals to said monitoring
and control system, a derived quantity layer communicatively coupled to a
data bus wherein the derived quantity layer is configured to receive the
measured process parameters; and compute values for process parameters
using the measured process parameters. The integrated monitoring and
control system also includes a rule set layer comprising at least one
rule associated with at least some of the plurality of equipment
combinations for determining a health of the equipment combination, and a
recommendation layer for correlating the health of the equipment
combination to at least one of a mitigating procedure, a maintaining
procedure, and an operation procedure.

[0006]In yet another aspect, a computer program embodied on a computer
readable medium for monitoring a plant is provided. The plant includes a
plurality of equipment combinations operating interactively with each
other and with individual equipment. The program includes a code segment
that controls a computer that receives a plurality of process parameters
from sensors operatively coupled to the equipment combinations and
individual equipment and then derives values for process parameters using
the measured process parameters, selects a rule from a set of rules
comprising a plurality of commands that direct data analysis for each at
least one of measured process parameter, a derived quantity, a plurality
of measured process parameters and a derived quantities associated with
an equipment combination, and recommends at least one of a mitigating
procedure, a maintaining procedure, and an operation procedure.

BRIEF DESCRIPTION OF THE DRAWINGS

[0007]FIG. 1 is a block diagram an exemplary equipment layout of an
industrial plant;

[0008]FIG. 2 is a block diagram of an exemplary embodiment of a network
architecture of a plant control system implementing the continuous
integrated machinery monitoring system (CIMMS) shown in FIG. 1;

[0009]FIG. 3 is a perspective view of an exemplary motor/pump combination
that may be one of a plurality driver/driven machine combinations
analyzed by the CIMMS shown in FIG. 1;

[0010]FIG. 4 is a block diagram of a data control structure that may be
used with the DCS to implement an exemplary embodiment of the CIMMS shown
in FIG. 1; and

[0011]FIG. 5 is a data flow diagram of an exemplary data flow path for
monitoring the equipment combination shown in FIG. 3.

DETAILED DESCRIPTION OF THE INVENTION

[0012]FIG. 1 is a block diagram an exemplary equipment layout of an
industrial plant 10. Industrial plant 10 may include a plurality of
pumps, motors, fans, and process monitoring sensors that are coupled in
flow communication through interconnecting piping and coupled in signal
communication with a control system through one or more remote
input/output (I/O) modules and interconnecting cabling and/or wireless
communication. In the exemplary embodiment, industrial plant 10 includes
a distributed control system (DCS) 20 including a network backbone 22.
Network backbone 22 may be a hardwired data communication path fabricated
from twisted pair cable, shielded coaxial cable or fiber optic cable, for
example, or may be at least partially wireless. DCS 20 may also include a
processor 24 that is communicatively coupled to equipment that is located
at industrial plant 10, or at remote locations, through network backbone
22. It is to be understood that any number of machines may be
communicatively connected to the network backbone 22. A portion of the
machines may be hardwired to network backbone 22, and another portion of
the machines may be wirelessly coupled to backbone 22 via a base station
26 that is communicatively coupled to DCS 20. Wireless base station 26
may be used to expand the effective communication range of DCS 20, such
as with equipment or sensors located remotely from industrial plant 10
but, still interconnected to one or more systems within industrial plant
10.

[0013]DCS 20 may be configured to receive and display operational
parameters associated with a plurality of equipment, and to generate
automatic control signals and receive manual control inputs for
controlling the operation of the equipment of industrial plant 10. In the
exemplary embodiment, DCS 20 may include a software code segment
configured to control processor 24 to analyze data received at DSC 20
that allows for on-line monitoring and diagnosis of the industrial plant
machines. Process parameter data may be collected from each machine,
including pumps and motors, associated process sensors, and local
environmental sensors, including for example, vibration, seismic, ambient
temperature and ambient humidity sensors. The data may be pre-processed
by a local diagnostic module or a remote input/output module, or may
transmitted to DCS 20 in raw form.

[0014]Specifically, industrial plant 10 may include a first process system
30 that includes a pump 32 coupled to a motor 34 through a coupling 36,
for example a hydraulic coupling, and interconnecting shafts 38. The
combination of pump 32, motor 34, and coupling 36, although comprising
separate components, may operate as a single system, such that conditions
affecting the operation of one component of the combination may effect
each of the other components of the combination. Accordingly, condition
monitoring data collected from one component of the combination that
indicates a failure of a portion of the component or an impending failure
of the component may be sensed at the other components of the combination
to confirm the failure of the component and/or facilitate determining a
source or root cause of the failure.

[0015]Pump 32 may be connected to a piping system 40 through one or more
valves 42. Valve 42 may include an actuator 44, for example, but, not
limited to, an air operator, a motor operator, and a solenoid. Actuator
44 may be communicatively coupled to DCS 20 for remote actuation and
position indication. In the exemplary embodiment, piping system 40 may
include process parameter sensors, such as a pressure sensor 46, a flow
sensor 48, a temperature sensor 50, and a differential pressure (DP)
sensor 52. In an alternative embodiment, piping system 40 may include
other sensors, such as turbidity, salinity, pH, specific gravity, and
other sensors associated with a particular fluid being carried by piping
system 40. Sensors 46, 48, 50 and 52 may be communicatively coupled to a
field module 54, for example, a preprocessing module, or remote I/O rack.

[0016]Motor 34 may include one or more of a plurality of sensors (not
shown) that are available to monitor the operating condition of
electrodynamic machines. Such sensors may be communicatively coupled to
field module 54 through an interconnecting conduit 56, for example,
copper wire or cable, fiber cable, and wireless technology.

[0017]Field module 54 may communicate with DCS 20 through a network
segment 58. The communications may be through any network protocol and
may be representative of preprocessed data and or raw data. The data may
be transmitted to processor 24 continuously in a real-time environment or
to processor 24 intermittently based on an automatic arrangement or a
request for data from processor 24. DCS 20 includes a real time clock in
communication with network backbone 22, for time stamping process
variables for time-based comparisons.

[0018]Piping system 40 may include other process components, such as a
tank 60 that may include one or more of a plurality of sensors available
for monitoring process parameters associated with tanks, such as, a tank
level sensor 62. Tank 60 may provide a surge volume for fluid pumped by
pump 32 and/or may provide suction pressure for downstream components,
such as, skid 64. Skid 64 may be a pre-engineered and prepackaged
subsystem of components that may be supplied by an OEM. Skid 64 may
include a first pump 66 and a second pump 68. In the exemplary
embodiment, first pump is coupled to a motor that is directly coupled to
a power source (not shown) through a circuit breaker (not shown) that may
be controlled by DCS 20. Second pump 68 is coupled to a motor 72 that is
coupled to the power source through a variable speed drive (VSD) 74 that
controls a rotational speed of motor 72 in response to commands from a
skid controller 76. Each of pumps 66 and 68, and motors 70 and 72, and
VSD 74 may include one or more sensors associated with respective
operating parameters of each type of equipment as described above in
relation to pump/motor/coupling 32, 34, and 36 combination. Skid
controller 76 receives signals from the sensors and may transmit the
signals to DCS 20 without preprocessing or after processing the data in
accordance with predetermined algorithms residing within skid controller
76. Skid controller 76 may also process the signals and generate control
signals for one or more of pumps 66 and 68, and motors 70 and 72, and VSD
74 without transmitting data to DCS 20. Skid controller may also receive
commands from DCS 20 to modify the operation of skid 64 in accordance
therewith.

[0019]A second piping system 80 may include a fan 82 that receives air
from an ambient space 84 and directs the air through a valve or damper 86
to a component, such as a furnace 88. Damper 86 may include position
sensors 90 and 92 to detect an open and closed position of damper 86.
Furnace 88 may include a damper 94 that may be operated by actuator 96,
which may be, for example, a motor actuator, a fluid powered piston
actuator, or other actuator, which may be controlled remotely by DCS 20
through a signal transmitted through a conduit (not shown). A second fan
98 may take a suction on furnace 88 to remove combustion gases from
furnace 88 and direct the combustion gases to a smoke stack or chimney
(not shown) for discharge to ambient space 84. Fan 98 may be driven by a
motor 100 through a shaft 102 coupled between fan 98 and motor 100. A
rotational speed of motor 100 may be controlled by a VSD 104 that may be
communicatively coupled to DCS 20 though network backbone 22. Fan 82 may
be driven by an engine 106, such as an internal combustion engine, or a
steam, water, wind, or gas turbine, or other driver, through a coupling
108, which may be hydraulic or other power conversion device. Each of the
components may include various sensors and control mechanisms that may be
communicatively coupled to DCS 20 through network backbone 22 or may
communicate with DCS 20 through a wireless transmitter/receiver 108 to
wireless base station 26.

[0020]DCS 20 may operate independently to control industrial plant 10, or
may be communicatively coupled to one or more other control systems 110.
Each control system may communicate with each other and DCS 20 through a
network segment 112, or may communicate through a network topology, for
example, a star (not shown).

[0021]A continuous integrated machinery monitoring system (CIMMS) 114 may
be a separate add-on hardware device that communicates with DCS 20 and
other control systems 110. CIMMS 114 may also be embodied in a software
program segment executing on DCS 20 and/or one or more of the other
control systems 110. Accordingly, CIMMS 114 may operate in a distributed
manner, such that a portion of the software program segment executes on
several processors concurrently. As such, CIMMS 114 may be fully
integrated into the operation of DCS 20 and other control systems 110.
CIMMS 114 analyzes data received by DCS 20 and the other control systems
110 determine a health the machines and/or a process employing the
machines using a global view of the industrial plant 10. CIMMS 114
analyzes combinations of drivers and driven components, and process
parameters associated with each combination to correlate machine health
findings of one machine to machine health indications from other machines
in the combination, and associated process or environmental data. CIMMS
114 uses direct measurements from various sensors available on each
machine and derived quantities from all or a portion of all the sensors
in industrial plant 10. CIMMS 114, using predetermined analysis rules,
determines a failure or impending failure of one machine and
automatically, in real-time correlates the data used to determine the
failure or impending failure with equivalent data derived from the
operating parameters of other components in the combination or from
process parameters. CIMMS 114 also provides for performing trend analysis
on the machine combinations and displaying data and/or trends in a
variety of formats so as to afford a user of CIMMS 114 an ability to
quickly interpret the health assessment and trend information provided by
CIMMS 114.

[0022]Although various combinations of machines are generally illustrated
as motor/pump, motor/fan, or engine/fan combinations, it should be
understood these combinations are exemplary only, and CIMMS is configured
to analyze any combination of driver/driven machines.

[0023]FIG. 2 is a block diagram of an exemplary embodiment of a network
architecture of a plant control system 200 implementing CIMMS 114 (shown
in FIG. 1). Components in system 200, identical to components of system
10 (shown in FIG. 1), are identified in FIG. 2 using the same reference
numerals as used in FIG. 1. In the exemplary embodiment, system 200
includes a server system 202 and client systems 204. Server system 202
further includes a database server 206, an application server 208, a web
server 210 a fax server 212, a directory server 214, and a mail server
216. Each of servers 206, 208, 210, 212, 214, and 216 may be embodied in
software executing on server system 202, or any combinations of servers
206, 208, 210, 212, 214, and 216 may be embodied alone or in combination
on separate server systems coupled in a local area network (LAN) (not
shown). A disk storage unit 220 is coupled to server system 202. In
addition, a workstation 222, such as a system administrator's
workstation, a user workstation, and/or a supervisor's workstation are
coupled to a LAN 224. Alternatively, workstations 222 are coupled to LAN
224 using an Internet link 226 or are connected through an Intranet.

[0024]Each workstation 222 may be a personal computer having a web
browser. Although the functions performed at the workstations typically
are illustrated as being performed at respective workstations 222, such
functions can be performed at one of many personal computers coupled to
LAN 224. Workstations 222 are described as being associated with separate
exemplary functions only to facilitate an understanding of the different
types of functions that can be performed by individuals having access to
LAN 224.

[0025]Server system 202 is configured to be communicatively coupled to
various individuals, including employees 228 and to third parties, e.g.,
service providers 230. The communication in the exemplary embodiment is
illustrated as being performed using the Internet, however, any other
wide area network (WAN) type communication can be utilized in other
embodiments, i.e., the systems and processes are not limited to being
practiced using the Internet.

[0026]In the exemplary embodiment, any authorized individual having a
workstation 232 can access CIMMS 114. At least one of the client systems
may include a manager workstation 234 located at a remote location.
Workstations 222 may be embodied on personal computers having a web
browser. Also, workstations 222 are configured to communicate with server
system 202. Furthermore, fax server 212 communicates with remotely
located client systems, including a client system 236 using a telephone
link (not shown). Fax server 212 is configured to communicate with other
client systems 228, 230, and 234, as well.

[0027]Computerized modeling and analysis tools of CIMMS 114, as described
below in more detail, are stored in server 202 and can be accessed by a
requester at any one of client systems 204. In one embodiment, client
systems 204 are computers including a web browser, such that server
system 202 is accessible to client systems 204 using the Internet. Client
systems 204 are interconnected to the Internet through many interfaces
including a network, such as a local area network (LAN) or a wide area
network (WAN), dial-in-connections, cable modems and special high-speed
ISDN lines. Client systems 204 could be any device capable of
interconnecting to the Internet including a web-based phone, personal
digital assistant (PDA), or other web-based connectable equipment.
Database server 206 is connected to a database 240 containing information
about industrial plant 10, as described below in greater detail. In one
embodiment, centralized database 240 is stored on server system 202 and
can be accessed by potential users at one of client systems 204 by
logging onto server system 202 through one of client systems 204. In an
alternative embodiment, database 240 is stored remotely from server
system 202 and may be non-centralized.

[0028]Other industrial plant systems may provide data that is accessible
to server system 202 and/or client systems 204 through independent
connections to LAN 224. An interactive electronic tech manual server 242
services requests for machine data relating to a configuration of each
machine. Such data may include operational capabilities, such as pump
curves, motor horsepower rating, insulation class, and frame size, design
parameters, such as dimensions, number of rotor bars or impeller blades,
and machinery maintenance history, such as field alterations to the
machine, as-found and as-left alignment measurements, and repairs
implemented on the machine that do not return the machine to its original
design condition. Additionally, server system 202 may send predetermined
and/or selectable setpoints to DCS 20. Such setpoint may be determined
based on a predetermined limitation on an equipment combination to limit
its capability based on a machinery history, as-found, and/or as left
inspection results. Other rule determinations may also transmitted to DCS
20.

[0029]A portable vibration monitor 244 may be intermittently coupled to
LAN directly or through a computer input port such as ports included in
workstations 222 or client systems 204. Typically, vibration data is
collected in a route, collecting data from a predetermined list of
machines on a periodic basis, for example, monthly or other periodicity.
Vibration data may also be collected in conjunction with troubleshooting,
maintenance, and commissioning activities. Such data may provide a new
baseline for algorithms of CIMMS 114. Process data may similarly, be
collected on a route basis or during troubleshooting, maintenance, and
commissioning activities. Certain process parameters may not be
permanently instrumented and a portable process data collector 244 may be
used to collect process parameter data that can be downloaded to plant
control system 200 so that it is accessible to CIMMS 114. Other process
parameter data, such as process fluid chemistry analyzers and pollution
emission analyzers may be provided to plant control system 200 through a
plurality of on-line monitors 246.

[0030]Electrical power supplied to various machines or generated by
generators within industrial plant 10 may be monitored by a relay 246,
for example, but, not limited to a protection relay, associated with each
machine. Typically, such relays 246 are located remotely from the
monitored equipment in a motor control center (MCC) or in switchgear 250
supplying the machine. In addition, to relay 246, switchgear 250 may also
include a supervisory control and data acquisition system (SCADA) that
provides CIMMS 114 with a condition of power supply or power delivery
system (not shown) equipment located at the industrial plant 10, for
example, in a switchyard, or remote transmission line breakers and line
parameters.

[0031]FIG. 3 is a perspective view of an exemplary motor/pump combination
300 that may be one of a plurality driver/driven machine combinations
analyzed by CIMMS 114. It should be understood that CIMMS 114 may be used
to monitor and analyze rotating equipment including pumps, turbines,
fans, blowers, compressors, non-rotating equipment, such as, transformers
and catalytic reactors, or other types of equipment. A pump and motor
combination is illustrated for purposes of example only. Pump and motor
combination 300 includes motor 302 and a pump 304. Motor 302 may be an
electric motor, diesel engine or turbine, or other power source. Motor
302 is operatively connected to pump 304 via coupling 16. Pump 304
includes an inlet 308 and an outlet 310. A control valve 311 may be
located downstream from outlet 310 of pump 304. Control valve 311 may be
responsive to commands received from DCS 20 for operating pump and motor
combination, 300 within selected operating design parameters. Control
valve 311 is also used to control flow through pump 304 to satisfy piping
and process system requirements. Closing control valve 311, by providing
a signal to a valve operator 313, increases fluid resistance to flow and
causes pump 304 to operate at a higher pressure and a lower flow rate.
Similarly, opening control valve 311 results in reduced fluid resistance,
increased flow rate and a relatively lower pressure.

[0032]A head tank (not shown) may be located upstream from inlet 308 of
pump 304. The head tank may include a level sensor and may provide pump
304 with sufficient head pressure to facilitate avoiding a cavitation
condition from occurring in pump 304. Process sensors may include an
outlet pressure sensor 312, which is positioned proximate outlet 310 of
pump 304, for determining pump outlet pressure. Process sensors may also
include a flowmeter 314 for determining a flow rate of a process fluid
downstream of pump 304, a temperature sensor 316, which is proximately
positioned upstream or downstream of pump 304 for determining temperature
of the process fluid, an inlet pressure sensor 318, which is positioned
proximate pump inlet 308 for determining rotating machine inlet pressure,
and a valve position sensor 320.

[0033]Valve position sensor 320 may be coupled to control valve 311 and
communicate with an input/output (I/O) device 322 for converting
electrical signals to digital signals, preprocessing sensor signals,
and/or to transmit the signals to DCS 20 as raw data. Valve position
sensor 320 is used to determine the position of control valve 311, and
valve position sensor 320 may provide input for a confirmatory method for
calculating flow through pump 304. Flow through valve 311 can be
calculated from a position of control valve 311, a pressure drop across
valve 311 and known fluid properties and pump geometry and/or a pump
curve supplied with the pump 304. The fluid properties, pump geometry,
and/or a pump curve may be stored in a database associated with CIMMS
114, such as, for example, on interactive electronic tech manual server
242. Flow through valve 311 may then be stored as original data. This
information enables a baseline head versus flow performance reference
curve to be developed in the absence of a pump curve supplied from the
pump supplier, and provides an alternate method to confirm operation of
sensors monitoring pump 304. For example, when flowmeter 314 fails, the
failure may be isolated to flowmeter 314 rather than a failure of pump
304 or other component of combination 300.

[0034]Additional sensors that may be used include, but are not limited to,
vibration sensors, which may be embodied in an accelerometer 324, other
vibration sensors may be proximity sensors, such as a pump outboard
proximity sensor 326, a pump inboard proximity sensor 328, a transducer a
once-per-revolution event, such as a Keyphasor® 330, and a thrust
sensor 332. Motor 302 may include a winding temperature sensor 334 for
determining an overheating and or overload condition in motor 302, a
bearing temperature sensor 336 to confirm an operating condition of a
motor bearing 338. A current and voltage of the electrical energy
supplied to motor 302 may be monitored locally or remotely at the MCC
supplying motor 302, or may be monitored by relay 246.

[0035]A variable speed drive (VSD) 340 may be electrically coupled to
motor 302 through a cable 342. VSD 340 may also be communicatively
coupled to DCS 20 to receive commands to change a rotational speed of
motor 302 to provide a selected flow and pressure.

[0036]FIG. 4 is a block diagram of a data control structure 400 that may
be used with DCS 20 to implement an exemplary embodiment of CIMMS 114
(shown in FIG. 1). DCS 20 may include CIMMS 114 executing on processor 24
within DCS 20. Alternatively, CIMMS 114 may operate separately form DCS
20 as a standalone processing platform, such as, a computer, workstation,
and/or client system processing machine.

[0038]Data received by communications layer 404 may be preprocessed by
communications layer 404 before being transmitted to data bus 406, and
data being transmitted by communications layer 404 to network backbone 22
may be post processed as needed for compatibility with various protocols
used by devices communicatively coupled to communications layer 404. DCS
20 may include a data processing layer 406 that is configured to receive
data from data bus 406. Data processing layer 406 may compare received
data values to predetermined limits, check for faulty instruments and
sensors. DCS 20 may also include an archive layer 408 wherein data may be
stored for later processing, trending, time-based analysis, and
outputting to output devices in a user selectable format. A data analyzer
layer 410 may be used to provide signal processing of data received
through communications layer 404. Such signal processing may include, but
is not limited to average, standard deviation, peak detection,
correlation, fast fourier transform (FFT), and demodulation. Specific
calculations may be mathematical algorithms, logical rule based, and/or
soft computing that exploit the tolerance for imprecision, uncertainty
and partial truth to achieve tractability, robustness and low solution
cost, including, for example, fuzzy logic, and/or neural network
processes involving multidimensional chains of calculations and
decisions. The calculations may also include statistical analyses and
database management processes. For some algorithms, calculations are
performed on the input parameters directly. Some algorithms may use data
transforms, that may be generated for a particular application, or use
standard techniques, such as, for example, various types of signal
analysis. Also, artificial intelligence based calculations may be used,
such as, rule-based methods for diagnosis of specific conditions, and/or
complex calculations based on neural networks that may be applied to
complex pattern recognition in signal analysis.

[0039]Data analyzer layer 410 may be embodied in software executing in DCS
20, or a separate analyzer communicatively coupled to data bas 406. Data
analyzer layer 410 may also be embodied in one or more hardware analyzers
such as, circuit cards, application specific integrated circuits (ASIC),
and/or analog or digital logic circuits.

[0040]CIMMS 114 may include a plurality of software layers 414
communicatively coupled to data bus 406. Software layers may include a
derived quantity layer 416 that may use data available in the DCS
hardware layers 402 to compute values for parameters that can not be
measured directly because, for example, the parameter is not
instrumented. For example, head loss remote from a point in a pipe that
is instrumented may be computed based on known values of pressure, flow,
fluid dynamics and piping characteristics. Each derived quantity may have
differing levels of certainty from each other based on the amount of data
available for computing that particular derived quantity, for example, a
pressure sensor used to compute one derived quantity may have a larger or
smaller accuracy compared to a pressure sensor used to compute another
derived quantity. Derived quantity layer 416 may use a plurality of
pressure sensors to compute a single derived quantity. Derived quantity
layer 416 may determine the derived quantity using the pressure sensor
that exhibits the greatest accuracy at the time of measurement. At a
later time, under different operating conditions, derived quantity layer
416 may select a different pressure sensor to compute the derived
quantity. Alternatively, derived quantity layer 416 may select both
pressure sensors to compute the derived quantity, but may weight each
pressure sensors contribution to the calculation based on an operating
condition of the system. Derived quantity layer 416 may compute a derived
quantity for any desired parameter in plant 10 that can be equated to one
or more measured parameters within plant 10.

[0041]Derived quantity layer 416 may also compute confirmatory sets of
data that relates to measured quantities in plant 10. For example,
derived quantity layer 416 may use measured process parameters received
from hardware layers 402 for comparison to values that are derived from
other measured process parameters and/or other derived quantities to
confirm operability and/or accuracy of sensors and/or data processing
devices. For example, vibration data received from a pump may indicate a
marked increase in one or more vibration parameters. Derived quantity
layer 416 may use measured and/or derived quantities, such as, but, not
limited to, pump flow, outlet pressure, motor current, and/or other
industrial plant measured parameters to confirm the nature of the problem
with the vibrating pump. Such an analysis occurs in real-time using
measured quantities of the associated motor/pump combination, other
system measured parameters, and/or derived quantities. Further analysis
may be initiated to increase the data available for pump diagnosis and/or
condition assessment. For example, derived quantity layer 416 may
transmit the received vibration data to a vibration analyzer for further
data extraction. The extracted data combined with the measured quantities
of the associated motor/pump combination, the other system measured
parameters, and/or the derived quantities may then be used to determine
the pump condition.

[0042]A rule set layer 418 includes a predefined set of rules for each
equipment combination 300 and each individual piece of equipment in
industrial plant 10. Such rule sets may take data for a given scenario,
for example, a motor/pump combination and automatically calculate and
determine performance or faults based on given inputs. Rule sets are a
grouping of rules based on domain knowledge that has been learned on the
machinery and performs a set of calculations and analysis without the
need for the domain knowledge expert.

[0043]A recommendation layer 420 monitors measured process parameters,
derived quantities, signal processing algorithms, analyzer outputs, and
accesses rule sets to determine trigger points for equipment conditions.
The trigger points are used to initiate actions, such as, recommending
additional data collection, for example from portable data collectors or
equipment not integrated into the DCS 20 or CIMMS 114. Other actions may
include recommending a mitigating procedure, such as a script of commands
that, if selected, may initiate mitigating steps, such as, shutting down
affected equipment, lining-up alternate flow paths, and starting up
equipment combinations that are redundant to the affected equipment.
Recommendation layer 420 may recommend a maintenance procedure that may
initiate commands to place an affected equipment combination in a
condition for performing maintenance activities on the equipment
combination. Additionally, recommendation layer 420 may use interaction
online technical manual to display design drawings and procedures to
maintenance personnel during a maintenance procedure so that manually
collecting data and inspection results may be updated immediately and be
made immediately available to plant engineering and operations personnel.
Recommendation layer 420 may use the entered manually collected data and
inspection results to apply other rules from rule set layer 418 to make
further recommendations. For example, a micrometer reading of a pump
shaft dimension may indicate a critical parameter has been exceeded and
that instead of a simple repair in the field, a shop rebuild is necessary
to return the pump to an operable condition. Recommendation layer 420 may
recommend an operating procedure as a result of evaluating measured
process parameters, derived quantities, and the rules stored in rule set
layer 418. The operating procedure may guide operating personnel through
a series of steps that may prolong the life, mean time between failures,
and/or extend operability to a next outage. Operating procedure may use
rule set 418 to recommend alternate operating cycles, expanding
operational limits to secondary limits, and postponing routine procedures
that stress affected equipment.

[0044]A display layer 422 generates display output that may be transmitted
to monitors, printers, data files, and/or other software modules for
analysis and/or forwarding to a pager and/or e-mail client. Display layer
422 may format the display output according to user selectable inputs.
Such displays may include, but are not limited to current values, a
bargraph, a machine train diagram, an alarm/system event list, a
trend/multivariable trend, a tabular list, a timebase, an orbit/timebase,
orbit, a shaft average centerline, a spectrum/full spectrum, an x vs. y,
waterfall/full waterfall, a polar/acceptance region, a bode, a
cascade/full cascade, a reciprocating compressor plot, a rod position, a
compressor map, a P-V diagram, a Log P versus Log V, a pressure versus
crank angle, a polar, and a phasor plot.

[0045]FIG. 5 is a data flow diagram of an exemplary data flow path for
monitoring an equipment combination 300 (shown in FIG. 3). Driver/driven
combination 300 includes a driver machine, such as a turbine, engine,
and/or motor 302, a driven machine, such as a generator, compressor,
and/or pump 304. Motor 302 and pump 304 are typically coupled together,
by their respective shafts, through a variable speed coupling, a gearbox,
a belt and pulley arrangement, or other coupling device (shown in FIG.
3). Motor 302 and pump 304 may be monitored by a suite of process,
environmental, and machine sensors (shown in FIG. 3). Outputs from these
sensors may be transmitted via various data collection instruments
through one or more data transmission conduits, for example, but not
limited to, a fiber optic cable 502, a copper cable 504, such as a
twisted pair cable, a wireless connection 506, and a digital network
segment 508. One or more data collection devices 510, 512, and 514
receive signals from the sensors and may preprocess at least a portion of
the signals before transmitting data representative of the sensor outputs
to DCS 20. Process data from a plurality of locations in industrial plant
10 may be collected using a field input/output (I/O) cabinet 516 that may
preprocess the process data before transmitting the process data to DCS
20. One or more databases may store offline data 518, for example, but
not limited to, machine nameplate data, industrial plant and component
design data, component maintenance history, including inspection results
and temporary operating limitations, and other periodically updateable
data that facilitates deriving operating parameters using measured
parameters.

[0046]DCS 20 is provided with predetermined logic for receiving measured
parameters from equipment located in industrial plant 10 or locally
remotely but, associated with industrial plant 10, and developing control
outputs to modify industrial plant equipment. A continuous integrated
machinery monitoring system CIMMS 114 may communicate bi-directionally
with DCS 20 over one or more network segments 520 or may be integral to
DCS 20 and execute on processor 24. CIMMS 114 includes a database of rule
sets that are configured to monitor industrial plant equipment using
measured parameters and derived quantities based on measured parameters
and offline data 518. The rule sets include rules that direct analysis of
rule set inputs and place a result of the analysis on outputs of the rule
set. Rule sets may include rules specific to a plant asset, such as a
motor/pump combination, or may include rules specific to an industrial
plant system, such as a cooling water system. Rule sets may be applied to
more than one plant asset and operate to relate the output of the rule
set to input parameters using one or more algorithms, signal processing
techniques, and/or waveform analysis parameters. When applied to a
specific plant asset, such as combination 300, the rules in rule set 280
use measured parameters and derived quantities for plant equipment and
driver/driven combinations that may be fluidly communicating with
combination 300 but are located remotely. As such, the derived quantities
associated with other plant equipment may be used to verify measured
parameters associated with combination 300 and provide information about
parameters associated with combination 300 that cannot be measured
directly due to, for example an absence of a sensor capable of measuring
the parameter or a sensor malfunction.

[0047]When a failure is detected and/or predicted, CIMMS 114 may provide
input to DCS 20 to initiate automatic control action to mitigate the
effects o the failure and/or may provide an operator with notification of
the failure and may generate a recommendation for action to be taken by
the operator.

[0048]A technical effect is to integrate monitoring and control functions
and expert system analysis into a decision system that operates with a
plurality of data sources for substituting derived quantities of process
parameters to facilitate analyzing equipment combination health and
verifying sensor health and accuracy. The integration allows rule sets to
govern monitoring, control, analysis, and maintenance by producing
recommendations based on continuously updated contemporaneous data to
ensure the best decision can be made. The rule sets are updateable based
on comparing actual findings in the field to recommended procedures.

[0049]While the present invention is described with reference to an
industrial plant, numerous other applications are contemplated. It is
contemplated that the present invention may be applied to any control
system, including facilities, such as commercial facilities, vehicles,
for example ships, aircraft, and trains, and office buildings or a campus
of buildings, as well as, refineries and midstream liquids facilities,
and facilities that produce discrete product outputs, such as, factories.

[0050]The above-described real-time equipment monitoring system is
cost-effective and highly reliable system for monitoring and managing the
operation and maintenance of facilities. More specifically, the methods
and systems described herein facilitate determining facility machine
health in real-time and recommending actions to correct or mitigate the
effect of unhealthy or failed machines. As a result, the methods and
systems described herein facilitate reducing operating costs in a
cost-effective and reliable manner.

[0051]Exemplary embodiments of real-time equipment monitoring systems are
described above in detail. The systems are not limited to the specific
embodiments described herein, but rather, components of each system may
be utilized independently and separately from other components described
herein. Each system component can also be used in combination with other
system components.

[0052]While the invention has been described in terms of various specific
embodiments, those skilled in the art will recognize that the invention
can be practiced with modification within the spirit and scope of the
claims.